[HTML][HTML] Operational research and artificial intelligence methods in banking
Banking is a popular topic for empirical and methodological research that applies
operational research (OR) and artificial intelligence (AI) methods. This article provides a …
operational research (OR) and artificial intelligence (AI) methods. This article provides a …
Artificial neural networks in business: Two decades of research
M Tkáč, R Verner - Applied Soft Computing, 2016 - Elsevier
In recent two decades, artificial neural networks have been extensively used in many
business applications. Despite the growing number of research papers, only few studies …
business applications. Despite the growing number of research papers, only few studies …
Forecasting stock price using integrated artificial neural network and metaheuristic algorithms compared to time series models
M Shahvaroughi Farahani, SH Razavi Hajiagha - Soft computing, 2021 - Springer
Today, stock market has important function and it can be a place as a measure of economic
position. People can earn a lot of money and return by investing their money in the stock …
position. People can earn a lot of money and return by investing their money in the stock …
Machine learning techniques for credit risk evaluation: a systematic literature review
Credit risk is the risk of financial loss when a borrower fails to meet the financial commitment.
While there are many factors that constitute credit risk, due diligence while giving loan (credit …
While there are many factors that constitute credit risk, due diligence while giving loan (credit …
Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring
In the recent decades, credit scoring has become a very important analytical resource for
researchers and financial institutions around the world. It helps to boost both profitability and …
researchers and financial institutions around the world. It helps to boost both profitability and …
Genetic algorithm-based heuristic for feature selection in credit risk assessment
S Oreski, G Oreski - Expert systems with applications, 2014 - Elsevier
In this paper, an advanced novel heuristic algorithm is presented, the hybrid genetic
algorithm with neural networks (HGA-NN), which is used to identify an optimum feature …
algorithm with neural networks (HGA-NN), which is used to identify an optimum feature …
Investigation and improvement of multi-layer perceptron neural networks for credit scoring
Abstract Multi-Layer Perceptron (MLP) neural networks are widely used in automatic credit
scoring systems with high accuracy and efficiency. This paper presents a higher accuracy …
scoring systems with high accuracy and efficiency. This paper presents a higher accuracy …
Ensemble learning or deep learning? Application to default risk analysis
S Hamori, M Kawai, T Kume, Y Murakami… - Journal of Risk and …, 2018 - mdpi.com
Proper credit-risk management is essential for lending institutions, as substantial losses can
be incurred when borrowers default. Consequently, statistical methods that can measure …
be incurred when borrowers default. Consequently, statistical methods that can measure …
Consumer credit risk assessment: A review from the state-of-the-art classification algorithms, data traits, and learning methods
Credit risk assessment is a crucial element in credit risk management. With the extensive
research on consumer credit risk assessment in recent decades, the abundance of literature …
research on consumer credit risk assessment in recent decades, the abundance of literature …
Mining semantic soft factors for credit risk evaluation in peer-to-peer lending
ABSTRACT While Peer-to-Peer (P2P) lending is rapidly growing, it is also accompanied by
high credit risk due to information asymmetry. Besides conventional hard information, soft …
high credit risk due to information asymmetry. Besides conventional hard information, soft …